'computational bottleneck' is a correct and usable phrase in written English.
It is used to describe when a process is slowed down or hindered due to an insufficient amount of computing resources available. For example, "The company found itself in a computational bottleneck when attempting to process the large influx of data."
In the previous work on rank-2 NMF [32] that takes a term-document matrix as input in the context of text clustering, sparse dense matrix multiplication (SpMM) was the main computational bottleneck for computing the solution.
The chip, based on a technique called in-memory computing, is designed to clear a primary computational bottleneck that forces computer processors to expend time and energy fetching data from stored memory.
One possible solution to the computational bottleneck during high volume periods might be to temporarily deploy more computing nodes, either on the local network, or using a computing grid solution.
The dispute centers on a fast-approaching computational bottleneck.
Methods to overcome this computational bottleneck have been a popular research topic for quite some time.
Training DNNs for event detection using the entire audio track from each video causes a computational bottleneck.
The resulting algorithm overcomes many of the computational bottlenecks associated with Markov chain Monte Carlo.
A study of weak and strong scaling behaviour, speedups and efficiency of the resulting program is presented including an investigation to elucidate the computational bottlenecks.
Given the complexity of the robot (large number of sensors and actuators) and fairly limited computatinal power, the controller must avoid computational bottlenecks that could compromise real-time performance.
Because arguably the biggest barriers to clinical genomics in healthcare is computational bottlenecks, I have focused my efforts on building new methods for genomic data processing that are fast, accurate, and cost effective.
In this paper we analyze the computational bottlenecks in discrete dislocation dynamics modeling (associated with segment–segment interactions as well as the treatment of free surfaces), discuss the parallelization and optimization strategies, and demonstrate the effectiveness of Graphical Processing Unit (GPU) computation in accelerating dislocation dynamics simulations and expanding their scope.
